NVIDIA adds CUDA-Q Logical quantum layer and 2M-GPU AWS deal; Huang forecasts 70% growth

CUDA-Q Logical adds a hardware-agnostic orchestration layer for fault-tolerant quantum workloads, extending NVIDIA's hybrid quantum-classical stack; quantum researchers cheered a claimed 7x speedup. The AWS deal commits 2 million additional GPUs to support agentic and physical AI workloads, deepening a partnership that also underpins AWS's broader AI infrastructure push. Huang's 70% growth forecast comes off a quarter of $96.2 billion in revenue, up 106% year over year.

One engineer's community math went viral: '70% on ~$200B base = ~$140B new revenue — constraining factor is TSMC CoWoS and HBM capacity, not demand.' That captures the prevailing view that NVIDIA's ceiling is supply, not orders, with advanced packaging and high-bandwidth memory the true bottlenecks. Huang's stance on governance also drew debate — an r/Anthropic thread flagged his 'we don't need AI regulation, leave safety to us' remark (85 upvotes).

Alongside the platform news, NVIDIA is pushing NIM microservices deeper into enterprise: Salesforce expanded Missionforce with NIM, Cloudera embedded NIM for on-prem inference, and NDI adopted LipSync NIM for real-time dubbing. The through-line is NVIDIA locking in the full stack — silicon, quantum orchestration, and inference software — as rivals like AMD and custom silicon (Meta's MTIA, Apple's M8 Ultra servers, AWS Trainium) chip at the edges. Watch whether the 2M-GPU AWS commitment signals hyperscalers doubling down on NVIDIA even as they build in-house alternatives.